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Proceedings Paper

Surface-based registration of liver in ultrasound and CT
Author(s): Ehsan Dehghan; Kongkuo Lu; Pingkun Yan; Amir Tahmasebi; Sheng Xu; Bradford J. Wood; Nadine Abi-Jaoudeh; Aradhana Venkatesan; Jochen Kruecker
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Paper Abstract

Ultrasound imaging is an attractive modality for real-time image-guided interventions. Fusion of US imaging with a diagnostic imaging modality such as CT shows great potential in minimally invasive applications such as liver biopsy and ablation. However, significantly different representation of liver in US and CT turns this image fusion into a challenging task, in particular if some of the CT scans may be obtained without contrast agents. The liver surface, including the diaphragm immediately adjacent to it, typically appears as a hyper-echoic region in the ultrasound image if the proper imaging window and depth setting are used. The liver surface is also well visualized in both contrast and non-contrast CT scans, thus making the diaphragm or liver surface one of the few attractive common features for registration of US and non-contrast CT. We propose a fusion method based on point-to-volume registration of liver surface segmented in CT to a processed electromagnetically (EM) tracked US volume. In this approach, first, the US image is pre-processed in order to enhance the liver surface features. In addition, non-imaging information from the EM-tracking system is used to initialize and constrain the registration process. We tested our algorithm in comparison with a manually corrected vessel-based registration method using 8 pairs of tracked US and contrast CT volumes. The registration method was able to achieve an average deviation of 12.8mm from the ground truth measured as the root mean square Euclidean distance for control points distributed throughout the US volume. Our results show that if the US image acquisition is optimized for imaging of the diaphragm, high registration success rates are achievable.

Paper Details

Date Published: 18 March 2015
PDF: 6 pages
Proc. SPIE 9415, Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling, 941522 (18 March 2015); doi: 10.1117/12.2082160
Show Author Affiliations
Ehsan Dehghan, Philips Research North America (United States)
Kongkuo Lu, Philips Research North America (United States)
Pingkun Yan, Philips Research North America (United States)
Amir Tahmasebi, Philips Research North America (United States)
Sheng Xu, National Institutes of Health (United States)
Bradford J. Wood, National Institutes of Health (United States)
Nadine Abi-Jaoudeh, National Institutes of Health (United States)
Aradhana Venkatesan, National Institutes of Health (United States)
Jochen Kruecker, Philips Research North America (United States)


Published in SPIE Proceedings Vol. 9415:
Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster; Ziv R. Yaniv, Editor(s)

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